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Automated Synthesisof SelectionOperators in GeneticAlgorithms usingGenetic Programming :научное издание Sopov E.Semenkin E.2017 год

Automated Synthesis of Selection Operators in Genetic Algorithms using Genetic Programming : научное издание
статья из журнала

Дополнительные ссылки: РИНЦ
База данных: Каталог библиотеки СФУ
Библиографическое описание: Automated Synthesis of Selection Operators in Genetic Algorithms using Genetic Programming : научное издание / E. Sopov, E. Semenkin. - Текст : непосредственный // № . - P. 13-24.
Аннотация: Genetic algorithms must be fine-tuned in order to achieve the best results. In this study, we have proposed a new hyper-heuristic based on genetic programming for the automated synthesis of a selection operator in genetic algorithms. Black-Box Optimization Benchmarking is used as a training set and as a test set for estimating the generalization ability of a synthesized selection operator. The results of numerical experiments for benchmark problems and a real-world problem are presented and discussed. The experiments have shown that the proposed approach can be used for designing new selection operators that outperform standard selection operators on average.
Год издания: 2017
Авторы: Sopov E. , Semenkin E.
Номера страниц: 13-24
Держатель оригинала документа: Reshetnev Siberian State University of Science and Technology
Количество экземпляров:
Твёрдая копия издания отсутствует в фонде библиотеки

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